Generalizability and accuracy of IBM MarketScan health risk assessment instrument data for augmentation of commercial claims data.
Journal
Pharmacoepidemiology and drug safety
ISSN: 1099-1557
Titre abrégé: Pharmacoepidemiol Drug Saf
Pays: England
ID NLM: 9208369
Informations de publication
Date de publication:
01 2022
01 2022
Historique:
revised:
14
09
2021
received:
20
04
2021
accepted:
13
10
2021
pubmed:
18
10
2021
medline:
4
1
2022
entrez:
17
10
2021
Statut:
ppublish
Résumé
We evaluated the generalizability and accuracy of the IBM® MarketScan® Health Risk Assessment (HRA) data to assess its suitability as supplement to linked claims data. We identified adult private insurance enrollees in the IBM® MarketScan® Commercial Claims & Encounters (CC&E) and HRA databases between 2012 and 2017. In the claims data, for each enrollee, we sampled the first calendar year with continuous enrollment indicating full capture of claims data and extracted linked HRA survey data if available. We compared HRA participants and non-participants considering demographics, prevalences of chronic conditions, and healthcare utilization. Including the subsample with HRA data only, we estimated the negative predictive value (NPV) of obesity and smoking reported in the HRA against diagnosis code in the claims data. Between 2012 and 2017, 2 693 444 and 31 450 000 of HRA and non-HRA participants were included in the study, respectively. Chronic diseases were similarly distributed between the two populations, with hypertension and hyperlipidemia representing the highest prevalence difference (1.4%). The two samples showed similar healthcare utilization. The proportion of false-negatives for obesity and smoking information when relying on the HRA data compared to patients with positive diagnosis based on claims data was low (<1%). Prevalence estimates of both variables were similar to national estimates. Our findings suggest that the overall HRA population may represent the overall claims population and HRA provides certain data elements with satisfactory accuracy.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
100-104Informations de copyright
© 2021 John Wiley & Sons Ltd.
Références
Huo J, Yang M, Tina Shih Y-C. Sensitivity of claims-based algorithms to ascertain smoking status more than doubled with meaningful use. Value Health. 2018;21(3):334-340. doi:10.1016/j.jval.2017.09.002
Lloyd JT, Blackwell SA, Wei II, Howell BL, Shrank WH. Validity of a claims-based diagnosis of obesity among medicare beneficiaries. Eval Health Prof. 2015;38(4):508-517. doi:10.1177/0163278714553661
Stürmer T, Schneeweiss S, Rothman KJ, Avorn J, Glynn RJ. Propensity score calibration and its alternatives. Am J Epidemiol. 2007;165(10):1122-1123. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2440716/
Choi J, Dekkers OM, le Cessie S. A comparison of different methods to handle missing data in the context of propensity score analysis. Eur J Epidemiol. 2019;34(1):23-36. doi:10.1007/s10654-018-0447-z
Thai TN, Sarayani A, Wang X, Albogami Y, Rasmussen SA, Winterstein AG. Risk of pregnancy loss in patients exposed to mycophenolate compared to azathioprine: a retrospective cohort study. Pharmacoepidemiol Drug Saf. 2020;29(6):716-724. doi:10.1002/pds.5017
Sarayani A, Albogami Y, Elkhider M, Hincapie-Castillo JM, Brumback BA, Winterstein AG. Comparative effectiveness of risk mitigation strategies to prevent fetal exposure to mycophenolate. BMJ Qual Saf. 2019;24:636-644. doi:10.1136/bmjqs-2019-010098
Coleman CI, Bunz TJ, Eriksson D, Meinecke A-K, Sood NA. Effectiveness and safety of rivaroxaban vs warfarin in people with non-valvular atrial fibrillation and diabetes: an administrative claims database analysis. Diabet Med. 2018;35(8):1105-1110. doi:10.1111/dme.13648
IBM MarketScan Research Databases for life sciences researchers. Accessed August 26, 2020. https://www.ibm.com/downloads/cas/0NKLE57Y
Glasheen WP, Cordier T, Gumpina R, Haugh G, Davis J, Renda A. Charlson comorbidity index: ICD-9 update and ICD-10 translation. Am Health Drug Benefits. 2019;12(4):188-197. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6684052/
Jackson CL, Wee CC, Hurtado DA, Kawachi I. Obesity trends by industry of employment in the United States, 2004 to 2011. BMC Obes. 2016;3(1):20. doi:10.1186/s40608-016-0100-x
Burden of Tobacco Use in the U.S. Centers for Disease Control and Prevention. Published July 23, 2020. Accessed August 26, 2020. https://www.cdc.gov/tobacco/campaign/tips/resources/data/cigarette-smoking-in-united-states.html
Yeager DS, Krosnick JA. The validity of self-reported nicotine product use in the 2001-2008 National Health and nutrition examination survey. Med Care. 2010;48(12):1128-1132. doi:10.1097/MLR.0b013e3181ef9948
Iii JT, Paulet M, Rajpura JR. Consistency between self-reported and recorded values for clinical measures. Cardiol Res Pract. 2016;2016:1-6. doi:10.1155/2016/4364761